Pritam Dash (University of British Columbia) and Karthik Pattabiraman (University of British Columbia)

Robotic Vehicles (RV) rely extensively on sensor inputs to operate autonomously. Physical attacks such as sensor tampering and spoofing feed erroneous sensor measurements to deviate RVs from their course and result in mission failures. We present PID-Piper , a novel framework for automatically recovering RVs from physical attacks. We use machine learning (ML) to design an attack resilient FeedForward Controller (FFC), which runs in tandem with the RV’s primary controller and monitors it. Under attacks, the FFC takes over from the RV’s primary controller to recover the RV, and allows the RV to complete its mission successfully. Our evaluation on 6 RV systems including 3 real RVs shows that PID-Piper allows RVs to complete their missions successfully despite attacks in 83% of the cases.

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PickMail: A Serious Game for Email Phishing Awareness Training

Gokul CJ (TCS Research, Tata Consultancy Services Ltd., Pune), Vijayanand Banahatti (TCS Research, Tata Consultancy Services Ltd., Pune), Sachin Lodha (TCS Research, Tata Consultancy Services Ltd., Pune)

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Transparency Dictionaries with Succinct Proofs of Correct Operation

Ioanna Tzialla (New York University), Abhiram Kothapalli (Carnegie Mellon University), Bryan Parno (Carnegie Mellon University), Srinath Setty (Microsoft Research)

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Phishing awareness and education – When to best remind?

Benjamin Maximilian Berens (SECUSO, Karlsruhe Institute of Technology), Katerina Dimitrova, Mattia Mossano (SECUSO, Karlsruhe Institute of Technology), Melanie Volkamer (SECUSO, Karlsruhe Institute of Technology)

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What the Fork? Finding and Analyzing Malware in GitHub...

Alan Cao (New York University) and Brendan Dolan-Gavitt (New York University)

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